Efficient Equilibrium Research Articles

Is pledge risk matched between pledgees and pledgers in China’s share pledge market?

Based on a sample of share pledging by the controlling shareholders of A-share listed firms, we investigate whether pledge risk is matched between pledgees and pledgers in China’s share pledge market. The results show that, compared with broker pledgees, commercial bank pledgees accept pledged stocks with lower market risk and the corresponding listed firms are at lower risk, have higher levels of information transparency and are more likely to be state-owned enterprises (SOEs). We also find that commercial bank pledgees do not ease the risk requirement of pledged stocks for pledgers of SOEs. Further, we document that commercial bank pledgees face lower margin call risks than broker pledgees. After securities companies were authorized to compete in the share pledge market in 2013, the pledge risk faced by commercial bank pledgees further reduced. Our results support that China’s share pledge financing market generally achieves an efficient equilibrium in terms of pledge risk matching between pledgees and pledgers. We recommend that the macro control of share pledge risk be focused on broker pledgees.

Coordination problems on networks revisited: statics and dynamics

Simple binary-state coordination models are widely used to study collective socio-economic phenomena such as the spread of innovations or the adoption of products on social networks. The common trait of these systems is the occurrence of large-scale coordination events taking place abruptly, in the form of a cascade process, as a consequence of small perturbations of an apparently stable state. The conditions for the occurrence of cascade instabilities have been largely analysed in the literature, however for the same coordination models no sufficient attention was given to the relation between structural properties of (Nash) equilibria and possible outcomes of dynamical equilibrium selection. Using methods from the statistical physics of disordered systems, the present work investigates both analytically and numerically, the statistical properties of such Nash equilibria on networks, focussing mostly on random graphs. We provide an accurate description of these properties, which is then exploited to shed light on the mechanisms behind the onset of coordination/miscoordination on large networks. This is done studying the most common processes of dynamical equilibrium selection, such as best response, bounded-rational dynamics and learning processes. In particular, we show that well beyond the instability region, full coordination is still globally stochastically stable, however equilibrium selection processes with low stochasticity (e.g. best response) or strong memory effects (e.g. reinforcement learning) can be prevented from achieving full coordination by being trapped into a large (exponentially in number of agents) set of locally stable Nash equilibria at low/medium coordination (inefficient equilibria). These results should be useful to allow a better understanding of general coordination problems on complex networks.

Comment on Iovino, La’O and Mascarenhas, “Optimal Monetary Policy and Disclosure with an Informationally-Constrained Central Banker”

Iovino, La’O and Mascarenhas (forthcoming) ask two important questions regarding the optimal conduct of monetary policy: Should the central bank’s policy depend on information the central bank has that is not available to markets? And should the central bank disclose information that it has but market participants do not? Iovino, La’O and Mascarenhas answer these questions using a simple, stylized model with one-period price stickiness. They show that efficient equilibria can be sustained regardless of whether policy depends on the central bank’s information and regardless of its disclosure policy. We explain the logic behind their irrelevance result and show that if restrictions are imposed on equilibria, then monetary policy should in general depend on the central banks information. Finally, we offer some speculative answers to their questions and discuss the sense in which policy is converging towards theory.

Rationality in games and institutions

Against the orthodox view of the Nash equilibrium as “the embodiment of the idea that economic agents are rational” (Aumann, 1985, p 43), some theorists have proposed ‘non-classical’ concepts of rationality in games, arguing that rational agents should be capable of improving upon inefficient equilibrium outcomes. This paper considers some implications of these proposals for economic theory, by focusing on institutional design. I argue that revisionist concepts of rationality conflict with the constraint that institutions should be designed to be incentive-compatible, that is, that they should implement social goals in equilibrium. To resolve this conflict, proponents of revisionist concepts face a choice between three options: (1) reject incentive compatibility as a general constraint, (2) deny that individuals interacting through the designed institutions are rational, or (3) accept that their concepts do not cover institutional design. I critically discuss these options and I argue that a more inclusive concept of rationality, e.g. the one provided by Robert Sugden’s version of team reasoning, holds the most promise for the non-classical project, yielding a novel argument for incentive compatibility as a general constraint.

Refinement of acyclic-and-asymmetric payoff aggregates of pure strategy efficient Nash equilibria in finite noncooperative games by maximultimin and superoptimality

A theory of refining pure strategy efficient Nash equilibria in finite noncooperative games under uncertainty is outlined. The theory is based on guaranteeing the corresponding payoffs for the players by using maximultimin, which is an expanded version of maximin. If a product of the players’ maximultimin subsets contains more than one efficient Nash equilibrium, a superoptimality rule is attached wherein minimization is substituted with summation. The superoptimality rule stands like a backup plan, and it is involved if maximultimin fails to produce just a single refined efficient equilibrium (a metaequilibrium). The number of the refinement possible outcomes is 10. There are 3 single-metaequilibrium cases, 3 partial reduction cases, and 4 fail cases. Despite successfulness of refinement drops as the game gets bigger, pessimistic estimation of its part is above 54 % for games with no more than four players.

An efficient equilibrium optimizer with support vector regression for stock market prediction

An efficient equilibrium optimizer with support vector regression for stock market prediction

Coordination Behavior in Mode Choice: Laboratory Study of Equilibrium Transformation and Selection

In a transportation system with multiple equilibria, coordination failure occurs when a group of travelers could achieve the efficient equilibrium but fail because they cannot coordinate their decision‐making under strategic uncertainty. This study investigated factors that might affect coordination behavior in mode choice with both positive and negative externalities. Subjects participated in a mode‐choice game in which they were required to choose between public transport and private car. Positive or negative externalities occurred when subjects chose public transport or private car, respectively, thereby generating two pure‐strategy equilibria in the mode‐choice game. The experimental results indicated that (i) the transparency of descriptive information facilitated not only the convergence to the efficient equilibrium but also the stabilization of choice behavior, (ii) historical experiences of converging to the inefficient equilibrium could affect subjects' initial choices and even equilibrium selection, and (iii) a “higher” barrier between the two equilibria impeded and prolonged the transformation from the inefficient equilibrium to the efficient equilibrium, and a “deeper” attraction basin of the efficient equilibrium was more attractive in equilibrium selection.

Absolute Versus Relative Success: Why Overconfidence Creates an Inefficient Equilibrium

Overconfidence is one of the most ubiquitous biases in the social sciences, but the evidence regarding its overall costs and benefits is mixed. To test the possibility that overconfidence might yield important relative benefits that offset its absolute costs, we conducted an experiment (N = 298 university students) in which pairs of participants bargained over the unequal allocation of a prize that was earned through a joint effort. We manipulated confidence using a binary noisy signal to investigate the causal effect of negotiators’ beliefs about their relative contribution to the outcome of the negotiation. Our results provide evidence that high levels of confidence lead to relative benefits (how much one earns compared with one’s partner) but absolute costs (how much money one receives overall). These results suggest that overconfidence creates an inefficient equilibrium whereby overconfident negotiators benefit over their partners even as they bring about joint losses.

On the inefficiency of perfect price discrimination

In a general equilibrium model with at least three goods, a perfectly price-discriminating monopoly (PDM) selects an inefficient production plan even if consumers are homogeneous, their preferences are representable by quasi-linear utilities, and their characteristics are known to the monopolist. In the same setting, regulation via a two-part tariff induces an efficient equilibrium allocation.

Learning how to dynamically route autonomous vehicles on shared roads

Road congestion induces significant costs across the world, and road network disturbances, such as traffic accidents, can cause highly congested traffic patterns. If a planner had control over the routing of all vehicles in the network, they could easily reverse this effect. In a more realistic scenario, we consider a planner that controls autonomous cars, which are a fraction of all present cars. We study a dynamic routing game, in which the route choices of autonomous cars can be controlled and the human drivers react selfishly and dynamically. As the problem is prohibitively large, we use deep reinforcement learning to learn a policy for controlling the autonomous vehicles. This policy indirectly influences human drivers to route themselves in such a way that minimizes congestion on the network. To gauge the effectiveness of our learned policies, we establish theoretical results characterizing equilibria and empirically compare the learned policy results with best possible equilibria. We prove properties of equilibria on parallel roads and provide a polynomial-time optimization for computing the most efficient equilibrium. Moreover, we show that in the absence of these policies, high demand and network perturbations would result in large congestion, whereas using the policy greatly decreases the travel times by minimizing the congestion. To the best of our knowledge, this is the first work that employs deep reinforcement learning to reduce congestion by indirectly influencing humans’ routing decisions in mixed-autonomy traffic.

On the Foundations of Competitive Search Equilibrium with and without Market Maker

The literature offers two foundations for competitive search equilibrium, a Nash approach and a market-maker approach. When each buyer visits only one seller (or each worker makes only one job application), the two approaches are equivalent. However, when each buyer visits multiple sellers, this equivalence can break down. Our paper analyzes competitive search equilibrium with simultaneous search using the two approaches. We consider four cases defined by (i) the surplus structure (are the goods substitutes or complements?) and (ii) the mechanism space (do sellers post fees or prices?). With fees, the two approaches yield the same constrained efficient equilibrium. With prices, the equilibrium allocation is the same using both approaches if the goods are complements, but is not constrained efficient. In the case in which only prices are posted and the goods are substitutes, the equilibrium allocations from the two approaches are different.

How market ecology explains market malfunction

Standard approaches to the theory of financial markets are based on equilibrium and efficiency. Here we develop an alternative based on concepts and methods developed by biologists, in which the wealth invested in a financial strategy is like the abundance of a species. We study a toy model of a market consisting of value investors, trend followers, and noise traders. We show that the average returns of strategies are strongly density dependent; that is, they depend on the wealth invested in each strategy at any given time. In the absence of noise, the market would slowly evolve toward an efficient equilibrium, but the statistical uncertainty in profitability (which is calibrated to match real markets) makes this noisy and uncertain. Even in the long term, the market spends extended periods of time away from perfect efficiency. We show how core concepts from ecology, such as the community matrix and food webs, give insight into market behavior. For example, at the efficient equilibrium, all three strategies have a mutualistic relationship, meaning that an increase in the wealth of one increases the returns of the others. The wealth dynamics of the market ecosystem explain how market inefficiencies spontaneously occur and gives insight into the origins of excess price volatility and deviations of prices from fundamental values.

Modified Schelling games

We introduce the class of modified Schelling games in which there are different types of agents who occupy the nodes of a location graph; agents of the same type are friends, and agents of different types are enemies. Every agent is strategic and jumps to empty nodes of the graph aiming to maximize her utility, defined as the ratio of her friends in her neighborhood over the neighborhood size including herself. This is in contrast to the related literature on Schelling games which typically assumes that an agent is excluded from her neighborhood whilst computing its size. Our model enables the utility function to capture likely cases where agents would rather be around a lot of friends instead of just a few, an aspect that was partially ignored in previous work. We provide a thorough analysis of the (in)efficiency of equilibria that arise in such modified Schelling games, by bounding the price of anarchy and price of stability for both general graphs and interesting special cases. Most of our results are tight and exploit the structure of equilibria as well as sophisticated constructions.

Trust between municipality and residents: A game-theory model for municipal solid-waste recycling efficiency

Efficient and sustainable municipal solid-waste management is a social, environmental, and economic challenge. One practice that enhances the success of municipal solid-waste management is building and operating a household separation at source infrastructure for recycling. In this study, we use game-theory tools to identify difficulties that a municipality and its residents face in building and operating infrastructure for recycling under the Extended Producer Responsibility law. The model presents a holistic and broad perspective on the social and economic parameters that affect the efficiency of recycling in a municipality. We explain the strategies available to players and the factors affecting the utilities gained by waste separation and recycling. We present several Nash equilibria in pure and mixed strategies and specify the coordination game conditions. The model identifies parameters and their effect on the decision to recycle. The study presents changes needed to streamline a recycling system for an efficient equilibrium.

Equilibria Under Negligence Liability

AbstractIn many accident contexts, the expected accident harm depends on observable as well as unobservable dimensions of the precaution exercised by the parties involved. The observable dimensions are commonly referred to as the ‘care’ levels and the unobservable aspects as the ‘activity’ levels. In a seminal contribution, Shavell, S (1980). Strict liability versus negligence. J. Leg. Stud. 9: 1–25 extended the scope of the economic analysis of liability rules by providing a model that allows for the care as well as activity level choices. Subsequent works have used and extended Shavell’s model to predict outcomes under various liability rules, and also to compare their efficiency properties. These works make several claims about the existence and efficiency of equilibria under different liability rules, without providing any formal proof. In this paper, we re-examine the prevalent claims in the literature using the standard model itself. Contrary to these prevalent claims, we show that the standard negligence liability rules do not induce equilibrium for all of the accident contexts admissible under the model. Under the standard model, even the ‘no-fault’ rules can fail to induce a Nash equilibrium. In the absence of an equilibrium, it is not plausible to make a claim about the efficiency of a ruleper-seorvis-a-visother rules. We show that even with commonly used utility functions that meet all of the requirements of the standard model, the social welfare function may not have a maximum. In many other situations fully compatible with the standard model, a maximum of the social welfare function is not discoverable by the first order conditions. Under the standard model, even individually optimum choices might not exist. We analyze the underlying problems with the standard model and offer some insights for future research on this subject.

Equilibrium Inefficiency and Computation in Cost-Sharing Games in Real-Time Scheduling Systems

We study cost-sharing games in real-time scheduling systems where the server’s activation cost in every time slot is a function of its load. We focus on monomial cost functions and consider both the case when the degree is less than one (inducing positive congestion effect for the jobs) and when it is greater than one (inducing negative congestion effect for the jobs). For the former case, we provide tight bounds on the price of anarchy, and show that the price of anarchy grows to infinity as a polynomial of the number of jobs in the game. For the latter, we observe that existing results provide constant and tight (asymptotically in the degree of the monomial) bounds on the price of anarchy. We then turn to analyze payment mechanism with arbitrary cost-sharing, that is, when the strategy of a player includes also its payment. We show that our mechanism reduces the price of anarchy of games with n jobs and unit server costs from Θ(n) to 2. We also show that, for a restricted class of instances, a similar improvement is achieved for monomial server costs. This is not the case, however, for unrestricted instances of monomial costs, for which we prove that the price of anarchy remains super-constant for our mechanism. For systems with load-independent activation costs, we show that our mechanism can produce an optimal solution which is stable against coordinated deviations.

An Efficient Decision-Making Approach for Short Term Indoor Room Temperature Forecasting in Smart Environment: Evidence from India

“Smart cities” start with “Smart Buildings” that improve the quality of urban services while ensuring sustainability. The current scenario in India reveals that the corporate and residential building structures are incorporating various self-sustainable techniques. Out of the multiple factors governing the comfort of smart buildings, indoor room temperature is an important one, since it drives the need of cooling or heating through controlling systems. Around one-third of total energy consumption of commercial buildings in India is attributed to Heating, Ventilation and Air Conditioning (HVAC) systems. Accurate prediction of indoor room temperature helps in creating an efficient equilibrium between energy consumption and comfort level of the building, thus providing opportunities for efficient decision making for energy optimization. Considering Indian climatic and geographical conditions, this paper proposes an efficient decision making approach using Bayesian Dynamic Models (BDM) for short-term indoor room temperature forecasting of a corporate building structure. The results obtained from Bayesian Dynamic linear model, using Expectation Maximization (EM) algorithm, have been compared to standard Auto Regressive Integrated Moving Average (ARIMA) model, and have been found to be more accurate. Forecasting of indoor room temperature is a highly nonlinear phenomenon, so to further improve the accuracy of the linear models, a hybrid modeling approach has been proposed. The inclusion of state-of-the-art nonlinear models such as Artificial Neural Networks (ANNs) and Support Vector Regression (SVR) improves the forecasting accuracy of the linear models significantly. Results show that the hybrid model obtained using BDM and ANN is the best fit model.

An Intelligent Algorithm for Solving the Efficient Nash Equilibrium of a Single-Leader Multi-Follower Game

This aim of this paper is to provide the immune particle swarm optimization (IPSO) algorithm for solving the single-leader–multi-follower game (SLMFG). Through cooperating with the particle swarm optimization (PSO) algorithm and an immune memory mechanism, the IPSO algorithm is designed. Furthermore, we define the efficient Nash equilibrium from the perspective of mathematical economics, which maximizes social welfare and further refines the number of Nash equilibria. In the end, numerical experiments show that the IPSO algorithm has fast convergence speed and high effectiveness.

A strictly economic explanation of gender roles: the lasting legacy of the plough

We show that the descendants of ancient farmers may have an interest in marrying among themselves, and thus maintaining the gendered division of labour originally justified on comparative-advantage grounds by the advent of the plough, even after they emigrate to a modern industrial economy where individual productivity depends on education rather than physical characteristics. The result rests on the argument that, if efficiency requires the more productive spouse to specialize in raising income, and the less productive one in raising children, irrespective of gender, an efficient domestic equilibrium will be implemented by a costlessly enforceable pre-marital contract stipulating that the husband should do the former and the wife the latter. A contract may not be needed, however, if time spent with children gives direct utility, because an efficient equilibrium may then be characterized by little or no division of labour.

Equilibria under Liability Rules: How the Standard Claims Fall Apart

In many accident contexts, the accident harm depends on observable as well as unobservable dimensions of the precaution exercised by the parties involved. The observable dimensions are commonly referred to as the `care' levels and the unobservable aspects as the `activity' levels. In a seminal contribution, Shavell (1980) extended the scope of economic analysis of liability rules by providing a model that allows for the care as well as activity level choices. Subsequent works have used and extended Shavell's model to predict outcomes under various liability rules and also to compare their efficiency properties. These works make several claims about the existence and efficiency of equilibria under different liability rules, without providing any formal proof. In this paper, we re-examine the prevalent claims in the literature using the standard model itself. Contrary to prevalent claims, we show that the standard negligence liability rules do not induce equilibrium for all the accident contexts admissible under the model. Under the standard model, even the `no-fault' rules can fail to induce a Nash equilibrium. In the absence of an equilibrium, it is not plausible to make a claim about efficiency of a rule per-se or vis-a-vis other rules. We show that even with commonly used utility functions that meet all the requirements of the standard model, the social welfare function may not have a maximum. In many other situations fully compatible with the standard models, a maximum of the social welfare function is not discoverable by the first order conditions. Under the standard models, even individually optimum choices might not exist. We analyze the underlying problems with the standard models and offer some insights for future research on this subject.